Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, mitigating the threat of bio-warfare, and understanding the factors that may be responsible for the fall of ancient civilizations.

In the industrial engineering community, it’s a well-known adage that focusing on process can help achieve better results. In this second of a series of papers, we’ll focus on the process of simulation testing and outline how improving your testing process can lead to better results for your projects. We’ll consider model building as a software development exercise, and discuss how best practices from the broader software testing community can be applied for process improvement.

Current IT related optimization efforts focus on optimizing IT level metrics such as response times, availability, etc. What the business requires is that such IT optimization be carried out so as to optimize business objectives. Such optimization is not a one-time effort as there may be significant changes, (e.g. server failures, sudden increase in the number of users) that may render any existing policy sub-optimal. Such optimization can be led in AnyLogic.

IRS Office of Research Headquarters measures and models taxpayer burden, defined as expenditures of time and money by taxpayers to comply with the federal tax system. In this research activity, IRS created two microsimulation models using econometric techniques to enable the Service to produce annual estimates of taxpayer compliance burden for individual and small business populations. Additionally, a Discrete Event Simulation (DES) model was developed to represent taxpayer activities and IRS administration in postfiling processes.

One of the approaches to modeling hybrid systems is to assign algebraic-differential equations describing the continuous behavior to states of state machines that represent discrete logic. The resulting hybrid state machine is a powerful concept to specify complex interdependencies between discrete and continuous time behaviors. It, however, exposes the simulation engine to a number of problems, which we discuss. The hybrid state machine based approach presented in this paper is fully supported by UML-RT/Java tool TimeBroker developed at Experimental Object Technologies.

We outline a modelling approach aimed to capture sophisticated interdependencies of discrete and continuous behaviors in hybrid systems. The approach is essentially a hybrid extension of widely recognized object-oriented languages UML and UML-RT. It is fully supported by a new simulation tool AnyLogic 4.0 from Experimental Object Technologies.

In this paper we give an overview of the car seat model that was developed for Daimler-Chrysler modeling contest in year 2001 and was awarded the 1st prize. We outline the OO UML-RT based modeling approach that was used and the simulation tool AnyLogic that supports it, and discuss their main advantages with respect to automotive area.

A large class of systems being developed has both continuous time and discrete time behavior. In fact, any system that interacts with physical world falls in that class. Chemical, Automotive, Military, Aerospace are areas most frequently mentioned in this respect. To model such systems successfully and to get accurate and reliable results from simulation experiments one needs an executable language naturally describing hybrid behavior, and a simulation engine capable of simulating discrete events interleaved with continuous time processes. Additional problems arise with simulating hybrid systems in a distributed environment.

We present a currently developed Decision Support Tool - Supply Chain (DST-SC). This is specialized domain oriented tool, which is an extension of the general purpose, UML-RT Hybrid Simulation kernel of AnyLogic by XJ Technologies. DST-SC allows high degree of flexibility with respect to the supply chain functionality being modeled, has the ability to handle large complex problems, and offers highly reusable model components, offering at the same time ease of use by non-experts in simulation.

In the old days, the price for IT services was formed in a pretty standardized way. Network services had an explicit usage price per Kbit/ sec. The range of provided IT services have been growing very fast and have reached new dimensions of complexity. From infrastructure pricing to web-enabled application availability and performance nowadays the old rules for defining service pricing is not applicable any more. Today it is difficult or sometime even impossible to associate the provided service levels with the cost related to the processes of operation, maintenance and the capital cost behind it. The old measures of dollars per Kbit/sec cannot be the right measure any more.